2025/06/12 by Ana Müller, Müller, Ana, Sabina Jeschke +3
Computer Science · Psychology · #AI in Service Interactions #FOS: Computer and information sciences #Robotics (cs.RO) #Social Robot Interaction and HRI #Speech and dialogue systems
paper · pdf · doi:10.48550/arxiv.2506.10462
openalex publication_date 2025/06/12 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
This paper investigates the impact of a group-adaptive conversation design in two socially interactive agents (SIAs) through two real-world studies. Both SIAs - Furhat, a social robot, and MetaHuman, a virtual agent - were equipped with a conversational artificial intelligence (CAI) backend combining hybrid retrieval and generative models. The studies were carried out in an in-the-wild setting with a total of N = 188 participants who interacted with the SIAs - in dyads, triads or larger groups - at a German museum. Although the results did not reveal a significant effect of the group-sensitive conversation design on perceived satisfaction, the findings provide valuable insights into the challenges of adapting CAI for multi-party interactions and across different embodiments (robot vs. virtual agent), highlighting the need for multimodal strategies beyond linguistic pluralization. These insights contribute to the fields of Human-Agent Interaction (HAI), Human-Robot Interaction (HRI), and broader Human-Machine Interaction (HMI), providing insights for future research on effective dialogue adaptation in group settings.